A glutamatergic network mediates lithium response in bipolar disorder as defined by epigenome pathway analysis
- PMID: 26343379
- DOI: 10.2217/pgs.15.106
A glutamatergic network mediates lithium response in bipolar disorder as defined by epigenome pathway analysis
Abstract
Aim: A regulatory network in the human brain mediating lithium response in bipolar patients was revealed by analysis of functional SNPs from genome-wide association studies (GWAS) and published gene association studies, followed by epigenome mapping.
Methods: An initial set of 23,312 SNPs in linkage disequilibrium with lead SNPs, and sub-threshold GWAS SNPs rescued by pathway analysis, were studied in the same populations. These were assessed using our workflow and annotation by the epigenome roadmap consortium.
Results: Twenty-seven percent of 802 SNPs that were associated with lithium response (13 published studies gene association studies and two GWAS) were shared in common with 1281 SNPs from 18 GWAS examining psychiatric disorders and adverse events associated with lithium treatment. Nineteen SNPs were annotated as active regulatory elements such as enhancers and promoters in a tissue-specific manner. They were located within noncoding regions of ten genes: ANK3, ARNTL, CACNA1C, CACNG2, CDKN1A, CREB1, GRIA2, GSK3B, NR1D1 and SLC1A2. Following gene set enrichment and pathway analysis, these genes were found to be significantly associated (p = 10(-27); Fisher exact test) with an AMPA2 glutamate receptor network in human brain. Our workflow results showed concordance with annotation of regulatory elements from the epigenome roadmap. Analysis of cognate mRNA and enhancer RNA exhibited patterns consistent with an integrated pathway in human brain.
Conclusion: This pharmacoepigenomic regulatory pathway is located in the same brain regions that exhibit tissue volume loss in bipolar disorder. Although in silico analysis requires biological validation, the approach provides value for identification of candidate variants that may be used in pharmacogenomic testing to identify bipolar patients likely to respond to lithium.
Keywords: bioinformatics; bipolar disorder; circadian rhythmicity; epigenome roadmap consortium; in silico analysis; lithium response; pharmacodynamics; pharmacoepigenomics.
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